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Record W2132370638 · doi:10.2337/dc13-0695

Risk of Breast Cancer by Individual Insulin Use: An International Multicenter Study

2013· article· en· W2132370638 on OpenAlexaffabout
Lamiae Grimaldi‐Bensouda, David Cameron, Michel Marty, Anthony Barnett, Frédérique Penault‐Llorca, Michaël Pollak, B Charbonnel, Matthew C. Riddle, L. Mignot, Jean‐François Boivin, Artak Khachatryan, Michel Rossignol, Jacques Bénichou, Annick Alpérovitch, Lucien Abenhaim

Bibliographic record

VenueDiabetes Care · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsJewish General HospitalMcGill University
FundersGlaxoSmithKlineAstraZenecaPfizer
KeywordsMedicineBreast cancerInsulin glargineInternal medicineType 2 diabetesOdds ratioDiabetes mellitusInsulinOncologyCancerGynecologyEndocrinology

Abstract

fetched live from OpenAlex

OBJECTIVE Several studies have been published in 2009 suggesting a possible association between insulin glargine and increased risk of malignancies, including breast cancer. The objective of this study was to assess the relation between the individual insulins (glargine, aspart, lispro, and human insulin) and development of breast cancer. RESEARCH DESIGN AND METHODS Seven hundred seventy-five incident cases of primary invasive or in situ carcinoma breast cancer occurring in women with diabetes from 92 centers in the U.K., Canada, and France were matched to a mean of 3.9 diabetic community control subjects (n = 3,050; recruited from 580 general practices) by country, age, recruitment date, and diabetes type and management. The main risk model was a multivariate conditional logistic regression model with case/control status as the dependent variable and individual insulin use, 8 years preceding the index date, as the independent variable, controlling for past use of any insulin, oral antidiabetes drugs, reproductive factors, lifestyle, education, hormone replacement therapy and history of contraceptive use, BMI, comorbidities, diabetes duration, and annual number of physician visits. Glargine was also compared with every other insulin by computing all ratios using the variance-covariance matrix of logistic model parameters. RESULTS Adjusted odds ratios of breast cancer for each type of insulin versus no use of that insulin were 1.04 (95% CI 0.76-1.44) for glargine, 1.23 (0.79-1.92) for lispro, 0.95 (0.64-1.40) for aspart, and 0.81 (0.55-1.20) for human insulin. Two-by-two comparisons found no difference between glargine and the different types of insulins. Insulin dosage or duration of use and tumor stage did not change the results. CONCLUSIONS This international study found no difference in the risk of developing breast cancer in patients with diabetes among the different types of insulin with short- to mid-term duration of use. Longer-term studies would be of interest.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.250
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2013
Admission routes2
Has abstractyes

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